Overview

Dataset statistics

Number of variables45
Number of observations761995
Missing cells21409356
Missing cells (%)62.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory261.6 MiB
Average record size in memory360.0 B

Variable types

Numeric40
Categorical5

Alerts

level_1 is highly correlated with ICULOSHigh correlation
O2Sat is highly correlated with SaO2High correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 5 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 6 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 2 other fieldsHigh correlation
PaCO2 is highly correlated with pHHigh correlation
SaO2 is highly correlated with O2SatHigh correlation
AST is highly correlated with BaseExcess and 2 other fieldsHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Alkalinephos is highly correlated with BaseExcess and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with AST and 1 other fieldsHigh correlation
Phosphate is highly correlated with BaseExcess and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with BaseExcess and 2 other fieldsHigh correlation
TroponinI is highly correlated with HCO3High correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1High correlation
level_1 is highly correlated with ICULOS and 1 other fieldsHigh correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 5 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 6 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 1 other fieldsHigh correlation
AST is highly correlated with BaseExcess and 1 other fieldsHigh correlation
BUN is highly correlated with Creatinine and 1 other fieldsHigh correlation
Alkalinephos is highly correlated with BaseExcess and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Lactate is highly correlated with BaseExcess and 1 other fieldsHigh correlation
Phosphate is highly correlated with BaseExcess and 3 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
TroponinI is highly correlated with HCO3High correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1 and 1 other fieldsHigh correlation
Sepsis is highly correlated with HoursHigh correlation
Hours is highly correlated with level_1 and 2 other fieldsHigh correlation
level_1 is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 4 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 5 other fieldsHigh correlation
pH is highly correlated with BaseExcess and 1 other fieldsHigh correlation
AST is highly correlated with BaseExcess and 1 other fieldsHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Alkalinephos is highly correlated with BaseExcessHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Phosphate is highly correlated with BaseExcess and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with HCO3 and 1 other fieldsHigh correlation
TroponinI is highly correlated with HCO3High correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1High correlation
Unit2 is highly correlated with Unit1High correlation
Unit1 is highly correlated with Unit2High correlation
HR has 92210 (12.1%) missing values Missing
O2Sat has 107657 (14.1%) missing values Missing
Temp has 503670 (66.1%) missing values Missing
SBP has 106064 (13.9%) missing values Missing
MAP has 112412 (14.8%) missing values Missing
DBP has 106257 (13.9%) missing values Missing
Resp has 161077 (21.1%) missing values Missing
EtCO2 has 704359 (92.4%) missing values Missing
BaseExcess has 760231 (99.8%) missing values Missing
HCO3 has 760584 (99.8%) missing values Missing
FiO2 has 744785 (97.7%) missing values Missing
pH has 745037 (97.8%) missing values Missing
PaCO2 has 744982 (97.8%) missing values Missing
SaO2 has 747594 (98.1%) missing values Missing
AST has 748632 (98.2%) missing values Missing
BUN has 719903 (94.5%) missing values Missing
Alkalinephos has 748586 (98.2%) missing values Missing
Calcium has 709982 (93.2%) missing values Missing
Chloride has 757306 (99.4%) missing values Missing
Creatinine has 719866 (94.5%) missing values Missing
Bilirubin_direct has 760187 (99.8%) missing values Missing
Glucose has 593135 (77.8%) missing values Missing
Lactate has 747692 (98.1%) missing values Missing
Magnesium has 725525 (95.2%) missing values Missing
Phosphate has 739590 (97.1%) missing values Missing
Potassium has 703306 (92.3%) missing values Missing
Bilirubin_total has 748547 (98.2%) missing values Missing
TroponinI has 748179 (98.2%) missing values Missing
Hct has 717620 (94.2%) missing values Missing
Hgb has 717225 (94.1%) missing values Missing
PTT has 754602 (99.0%) missing values Missing
WBC has 721896 (94.7%) missing values Missing
Fibrinogen has 757783 (99.4%) missing values Missing
Platelets has 721285 (94.7%) missing values Missing
Unit1 has 225795 (29.6%) missing values Missing
Unit2 has 225795 (29.6%) missing values Missing
FiO2 is highly skewed (γ1 = 131.1114503) Skewed
level_1 has 20000 (2.6%) zeros Zeros
HospAdmTime has 49742 (6.5%) zeros Zeros

Reproduction

Analysis started2021-11-29 18:21:41.178423
Analysis finished2021-11-29 18:23:28.612485
Duration1 minute and 47.43 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

Distinct20000
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110025.3176
Minimum100001
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:28.738198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum100001
5-th percentile100984
Q1105047
median110058
Q3115003
95-th percentile119024
Maximum120000
Range19999
Interquartile range (IQR)9956

Descriptive statistics

Standard deviation5776.257876
Coefficient of variation (CV)0.052499352
Kurtosis-1.19402897
Mean110025.3176
Median Absolute Deviation (MAD)4979
Skewness-0.003565541124
Sum8.383874187 × 1010
Variance33365155.05
MonotonicityIncreasing
2021-11-29T19:23:29.030165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113190336
 
< 0.1%
114471336
 
< 0.1%
116439336
 
< 0.1%
101922336
 
< 0.1%
117406336
 
< 0.1%
111353335
 
< 0.1%
111709335
 
< 0.1%
111512334
 
< 0.1%
113429333
 
< 0.1%
100134327
 
< 0.1%
Other values (19990)758651
99.6%
ValueCountFrequency (%)
10000124
< 0.1%
10000225
< 0.1%
10000343
< 0.1%
10000459
< 0.1%
10000552
< 0.1%
10000647
< 0.1%
10000737
< 0.1%
10000850
< 0.1%
10000930
< 0.1%
10001016
 
< 0.1%
ValueCountFrequency (%)
12000035
< 0.1%
11999920
< 0.1%
11999849
< 0.1%
11999725
< 0.1%
11999648
< 0.1%
11999542
< 0.1%
11999442
< 0.1%
11999321
< 0.1%
11999241
< 0.1%
11999125
< 0.1%

level_1
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct336
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.6589807
Minimum0
Maximum335
Zeros20000
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:29.327271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median19
Q333
95-th percentile63
Maximum335
Range335
Interquartile range (IQR)24

Descriptive statistics

Standard deviation29.81392567
Coefficient of variation (CV)1.161929463
Kurtosis24.65520099
Mean25.6589807
Median Absolute Deviation (MAD)11
Skewness4.160860095
Sum19552015
Variance888.8701636
MonotonicityNot monotonic
2021-11-29T19:23:29.592998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020000
 
2.6%
120000
 
2.6%
220000
 
2.6%
320000
 
2.6%
420000
 
2.6%
520000
 
2.6%
620000
 
2.6%
720000
 
2.6%
819796
 
2.6%
919682
 
2.6%
Other values (326)562517
73.8%
ValueCountFrequency (%)
020000
2.6%
120000
2.6%
220000
2.6%
320000
2.6%
420000
2.6%
520000
2.6%
620000
2.6%
720000
2.6%
819796
2.6%
919682
2.6%
ValueCountFrequency (%)
3355
< 0.1%
3347
< 0.1%
3338
< 0.1%
3329
< 0.1%
3319
< 0.1%
3309
< 0.1%
3299
< 0.1%
3289
< 0.1%
3279
< 0.1%
32610
< 0.1%

HR
Real number (ℝ≥0)

MISSING

Distinct311
Distinct (%)< 0.1%
Missing92210
Missing (%)12.1%
Infinite0
Infinite (%)0.0%
Mean84.14190524
Minimum20
Maximum211
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:29.873487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile58
Q171.5
median83
Q395
95-th percentile115
Maximum211
Range191
Interquartile range (IQR)23.5

Descriptive statistics

Standard deviation17.72415968
Coefficient of variation (CV)0.2106460465
Kurtosis0.3646264269
Mean84.14190524
Median Absolute Deviation (MAD)12
Skewness0.4495574579
Sum56356986
Variance314.1458365
MonotonicityNot monotonic
2021-11-29T19:23:30.137409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8021293
 
2.8%
9020061
 
2.6%
8216673
 
2.2%
8416026
 
2.1%
7815972
 
2.1%
7415670
 
2.1%
7615325
 
2.0%
7215197
 
2.0%
8615154
 
2.0%
7015138
 
2.0%
Other values (301)503276
66.0%
(Missing)92210
 
12.1%
ValueCountFrequency (%)
203
 
< 0.1%
212
 
< 0.1%
222
 
< 0.1%
231
 
< 0.1%
23.51
 
< 0.1%
244
 
< 0.1%
257
 
< 0.1%
2625
< 0.1%
26.51
 
< 0.1%
274
 
< 0.1%
ValueCountFrequency (%)
2111
 
< 0.1%
1941
 
< 0.1%
1912
 
< 0.1%
1881
 
< 0.1%
1869
< 0.1%
18414
< 0.1%
1831
 
< 0.1%
182.51
 
< 0.1%
1828
< 0.1%
181.51
 
< 0.1%

O2Sat
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct131
Distinct (%)< 0.1%
Missing107657
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean97.11774878
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:30.420416image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile92
Q196
median98
Q399.5
95-th percentile100
Maximum100
Range80
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.964617576
Coefficient of variation (CV)0.03052601212
Kurtosis51.73268616
Mean97.11774878
Median Absolute Deviation (MAD)2
Skewness-3.736983633
Sum63547833.5
Variance8.788957374
MonotonicityNot monotonic
2021-11-29T19:23:30.688768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100156535
20.5%
9884666
11.1%
9978001
10.2%
9777140
10.1%
9666649
8.7%
9551802
 
6.8%
9435928
 
4.7%
9322665
 
3.0%
9214398
 
1.9%
99.58406
 
1.1%
Other values (121)58148
 
7.6%
(Missing)107657
14.1%
ValueCountFrequency (%)
2012
< 0.1%
214
 
< 0.1%
225
< 0.1%
233
 
< 0.1%
246
< 0.1%
263
 
< 0.1%
271
 
< 0.1%
282
 
< 0.1%
293
 
< 0.1%
303
 
< 0.1%
ValueCountFrequency (%)
100156535
20.5%
99.58406
 
1.1%
9978001
10.2%
98.57927
 
1.0%
9884666
11.1%
97.57646
 
1.0%
9777140
10.1%
96.56668
 
0.9%
9666649
8.7%
95.55464
 
0.7%

Temp
Real number (ℝ≥0)

MISSING

Distinct209
Distinct (%)0.1%
Missing503670
Missing (%)66.1%
Infinite0
Infinite (%)0.0%
Mean36.92607587
Minimum30
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:30.976018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile35.8
Q136.5
median36.9
Q337.4
95-th percentile38.1
Maximum50
Range20
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation0.7558255072
Coefficient of variation (CV)0.02046861166
Kurtosis3.580449366
Mean36.92607587
Median Absolute Deviation (MAD)0.5
Skewness-0.2282658806
Sum9538928.55
Variance0.5712721974
MonotonicityNot monotonic
2021-11-29T19:23:31.257010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3715852
 
2.1%
36.815434
 
2.0%
36.614496
 
1.9%
36.714085
 
1.8%
36.513958
 
1.8%
37.212578
 
1.7%
36.912471
 
1.6%
37.111778
 
1.5%
36.411257
 
1.5%
37.410773
 
1.4%
Other values (199)125643
 
16.5%
(Missing)503670
66.1%
ValueCountFrequency (%)
304
< 0.1%
30.11
 
< 0.1%
30.41
 
< 0.1%
30.52
< 0.1%
30.61
 
< 0.1%
30.71
 
< 0.1%
30.82
< 0.1%
30.93
< 0.1%
311
 
< 0.1%
31.11
 
< 0.1%
ValueCountFrequency (%)
502
< 0.1%
42.11
 
< 0.1%
421
 
< 0.1%
41.82
< 0.1%
41.52
< 0.1%
41.43
< 0.1%
41.33
< 0.1%
41.251
 
< 0.1%
41.23
< 0.1%
41.151
 
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct792
Distinct (%)0.1%
Missing106064
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean126.5984327
Minimum20
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:31.774783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile91
Q1109
median124
Q3142
95-th percentile170
Maximum300
Range280
Interquartile range (IQR)33

Descriptive statistics

Standard deviation24.53301794
Coefficient of variation (CV)0.1937861111
Kurtosis0.3582686173
Mean126.5984327
Median Absolute Deviation (MAD)17
Skewness0.4990027314
Sum83039836.53
Variance601.868969
MonotonicityNot monotonic
2021-11-29T19:23:32.029336image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11611249
 
1.5%
11811064
 
1.5%
11410808
 
1.4%
12010801
 
1.4%
12410739
 
1.4%
11210716
 
1.4%
11010572
 
1.4%
12210471
 
1.4%
12810181
 
1.3%
12610168
 
1.3%
Other values (782)549162
72.1%
(Missing)106064
 
13.9%
ValueCountFrequency (%)
205
< 0.1%
212
 
< 0.1%
225
< 0.1%
244
< 0.1%
254
< 0.1%
271
 
< 0.1%
281
 
< 0.1%
291
 
< 0.1%
304
< 0.1%
311
 
< 0.1%
ValueCountFrequency (%)
3001
 
< 0.1%
2991
 
< 0.1%
2981
 
< 0.1%
2963
< 0.1%
2951
 
< 0.1%
2941
 
< 0.1%
2932
< 0.1%
2922
< 0.1%
2911
 
< 0.1%
2902
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct418
Distinct (%)0.1%
Missing112412
Missing (%)14.8%
Infinite0
Infinite (%)0.0%
Mean86.36713707
Minimum30
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:32.295594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile63
Q174.5
median84
Q396
95-th percentile116
Maximum300
Range270
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation16.7744491
Coefficient of variation (CV)0.1942225905
Kurtosis4.514985383
Mean86.36713707
Median Absolute Deviation (MAD)11
Skewness1.00239841
Sum56102624
Variance281.3821426
MonotonicityNot monotonic
2021-11-29T19:23:32.567659image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7817619
 
2.3%
8017212
 
2.3%
8217130
 
2.2%
8416836
 
2.2%
7616818
 
2.2%
8616091
 
2.1%
8816029
 
2.1%
7415897
 
2.1%
7214709
 
1.9%
7914393
 
1.9%
Other values (408)486849
63.9%
(Missing)112412
 
14.8%
ValueCountFrequency (%)
3011
 
< 0.1%
3116
< 0.1%
3225
< 0.1%
3325
< 0.1%
3414
< 0.1%
34.52
 
< 0.1%
3516
< 0.1%
35.51
 
< 0.1%
3633
< 0.1%
36.54
 
< 0.1%
ValueCountFrequency (%)
3004
< 0.1%
2986
< 0.1%
2963
< 0.1%
2951
 
< 0.1%
2945
< 0.1%
2932
 
< 0.1%
2922
 
< 0.1%
2913
< 0.1%
2906
< 0.1%
2884
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct609
Distinct (%)0.1%
Missing106257
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean66.2340016
Minimum20
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:32.828318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile46
Q156
median65
Q374
95-th percentile91
Maximum300
Range280
Interquartile range (IQR)18

Descriptive statistics

Standard deviation14.23701638
Coefficient of variation (CV)0.2149502677
Kurtosis6.207585886
Mean66.2340016
Median Absolute Deviation (MAD)9
Skewness1.06344583
Sum43432151.74
Variance202.6926353
MonotonicityNot monotonic
2021-11-29T19:23:33.082310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5822293
 
2.9%
6021722
 
2.9%
5620509
 
2.7%
6219907
 
2.6%
6419586
 
2.6%
6618556
 
2.4%
5917869
 
2.3%
6317863
 
2.3%
6817650
 
2.3%
7017472
 
2.3%
Other values (599)462311
60.7%
(Missing)106257
 
13.9%
ValueCountFrequency (%)
2025
< 0.1%
20.53
 
< 0.1%
2126
< 0.1%
21.57
 
< 0.1%
2235
< 0.1%
22.51
 
< 0.1%
2328
< 0.1%
23.56
 
< 0.1%
2456
< 0.1%
24.54
 
< 0.1%
ValueCountFrequency (%)
3002
< 0.1%
2981
 
< 0.1%
2963
< 0.1%
2932
< 0.1%
2922
< 0.1%
2912
< 0.1%
2902
< 0.1%
2881
 
< 0.1%
2871
 
< 0.1%
2851
 
< 0.1%

Resp
Real number (ℝ≥0)

MISSING

Distinct151
Distinct (%)< 0.1%
Missing161077
Missing (%)21.1%
Infinite0
Infinite (%)0.0%
Mean18.67078037
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:33.366752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12
Q116
median18
Q321
95-th percentile27
Maximum100
Range99
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.72029401
Coefficient of variation (CV)0.2528171783
Kurtosis8.873033573
Mean18.67078037
Median Absolute Deviation (MAD)2.5
Skewness1.117172153
Sum11219608
Variance22.28117554
MonotonicityNot monotonic
2021-11-29T19:23:33.641819image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1882460
10.8%
2075167
9.9%
1667922
8.9%
2239291
 
5.2%
1434824
 
4.6%
1534406
 
4.5%
1733311
 
4.4%
1930116
 
4.0%
2125478
 
3.3%
2423354
 
3.1%
Other values (141)154589
20.3%
(Missing)161077
21.1%
ValueCountFrequency (%)
1447
0.1%
1.556
 
< 0.1%
2634
0.1%
2.551
 
< 0.1%
3371
< 0.1%
3.542
 
< 0.1%
4371
< 0.1%
4.538
 
< 0.1%
5296
< 0.1%
5.526
 
< 0.1%
ValueCountFrequency (%)
1005
< 0.1%
997
< 0.1%
986
< 0.1%
975
< 0.1%
96.51
 
< 0.1%
965
< 0.1%
954
< 0.1%
943
< 0.1%
934
< 0.1%
922
 
< 0.1%

EtCO2
Real number (ℝ≥0)

MISSING

Distinct139
Distinct (%)0.2%
Missing704359
Missing (%)92.4%
Infinite0
Infinite (%)0.0%
Mean32.95765667
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:33.915701image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile19
Q128
median33
Q338
95-th percentile45
Maximum100
Range90
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.951662124
Coefficient of variation (CV)0.2412690381
Kurtosis4.962535523
Mean32.95765667
Median Absolute Deviation (MAD)5
Skewness0.496014827
Sum1899547.5
Variance63.22893053
MonotonicityNot monotonic
2021-11-29T19:23:34.177304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
352930
 
0.4%
342901
 
0.4%
322842
 
0.4%
332814
 
0.4%
312573
 
0.3%
302493
 
0.3%
362463
 
0.3%
372356
 
0.3%
292305
 
0.3%
382162
 
0.3%
Other values (129)31797
 
4.2%
(Missing)704359
92.4%
ValueCountFrequency (%)
10138
< 0.1%
10.531
 
< 0.1%
11116
< 0.1%
11.527
 
< 0.1%
12179
< 0.1%
12.529
 
< 0.1%
13183
< 0.1%
13.543
 
< 0.1%
14208
< 0.1%
14.560
 
< 0.1%
ValueCountFrequency (%)
10012
< 0.1%
994
 
< 0.1%
9813
< 0.1%
9712
< 0.1%
964
 
< 0.1%
952
 
< 0.1%
942
 
< 0.1%
932
 
< 0.1%
924
 
< 0.1%
861
 
< 0.1%

BaseExcess
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct345
Distinct (%)19.6%
Missing760231
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean-2.669217687
Minimum-23.2
Maximum14.2
Zeros11
Zeros (%)< 0.1%
Negative1338
Negative (%)0.2%
Memory size5.8 MiB
2021-11-29T19:23:34.443920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-23.2
5-th percentile-9.685
Q1-4.9
median-2.4
Q3-0.2
95-th percentile3.5425
Maximum14.2
Range37.4
Interquartile range (IQR)4.7

Descriptive statistics

Standard deviation4.185395734
Coefficient of variation (CV)-1.568023378
Kurtosis1.94197408
Mean-2.669217687
Median Absolute Deviation (MAD)2.35
Skewness-0.4512115017
Sum-4708.5
Variance17.51753745
MonotonicityNot monotonic
2021-11-29T19:23:34.713409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.127
 
< 0.1%
0.523
 
< 0.1%
-0.423
 
< 0.1%
-322
 
< 0.1%
-0.922
 
< 0.1%
-0.522
 
< 0.1%
-2.421
 
< 0.1%
-4.521
 
< 0.1%
-3.921
 
< 0.1%
-3.420
 
< 0.1%
Other values (335)1542
 
0.2%
(Missing)760231
99.8%
ValueCountFrequency (%)
-23.21
< 0.1%
-22.11
< 0.1%
-21.81
< 0.1%
-21.21
< 0.1%
-18.91
< 0.1%
-18.251
< 0.1%
-17.81
< 0.1%
-17.41
< 0.1%
-171
< 0.1%
-16.61
< 0.1%
ValueCountFrequency (%)
14.21
 
< 0.1%
13.31
 
< 0.1%
11.61
 
< 0.1%
11.11
 
< 0.1%
10.91
 
< 0.1%
10.21
 
< 0.1%
9.11
 
< 0.1%
91
 
< 0.1%
8.53
< 0.1%
8.41
 
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct265
Distinct (%)18.8%
Missing760584
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean23.21906449
Minimum7.7
Maximum36.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:34.989836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7.7
5-th percentile18
Q121.45
median23.4
Q325.1
95-th percentile28.25
Maximum36.4
Range28.7
Interquartile range (IQR)3.65

Descriptive statistics

Standard deviation3.259499175
Coefficient of variation (CV)0.1403802972
Kurtosis1.998719286
Mean23.21906449
Median Absolute Deviation (MAD)1.85
Skewness-0.2423278155
Sum32762.1
Variance10.62433487
MonotonicityNot monotonic
2021-11-29T19:23:35.241861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.325
 
< 0.1%
23.522
 
< 0.1%
21.822
 
< 0.1%
23.822
 
< 0.1%
24.521
 
< 0.1%
24.621
 
< 0.1%
22.620
 
< 0.1%
24.320
 
< 0.1%
23.920
 
< 0.1%
23.219
 
< 0.1%
Other values (255)1199
 
0.2%
(Missing)760584
99.8%
ValueCountFrequency (%)
7.71
< 0.1%
8.41
< 0.1%
9.91
< 0.1%
10.951
< 0.1%
11.41
< 0.1%
121
< 0.1%
12.452
< 0.1%
12.61
< 0.1%
13.11
< 0.1%
13.31
< 0.1%
ValueCountFrequency (%)
36.41
 
< 0.1%
36.31
 
< 0.1%
361
 
< 0.1%
35.31
 
< 0.1%
342
< 0.1%
33.91
 
< 0.1%
33.71
 
< 0.1%
32.91
 
< 0.1%
32.41
 
< 0.1%
323
< 0.1%

FiO2
Real number (ℝ)

MISSING
SKEWED

Distinct92
Distinct (%)0.5%
Missing744785
Missing (%)97.7%
Infinite0
Infinite (%)0.0%
Mean0.7411597908
Minimum-50
Maximum4000
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)< 0.1%
Memory size5.8 MiB
2021-11-29T19:23:35.725471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-50
5-th percentile0.21
Q10.4
median0.4
Q30.6
95-th percentile1
Maximum4000
Range4050
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation30.49277809
Coefficient of variation (CV)41.14197569
Kurtosis17196.89811
Mean0.7411597908
Median Absolute Deviation (MAD)0.1
Skewness131.1114503
Sum12755.36
Variance929.8095159
MonotonicityNot monotonic
2021-11-29T19:23:36.000463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.45306
 
0.7%
0.52814
 
0.4%
12168
 
0.3%
0.211471
 
0.2%
0.61012
 
0.1%
0.7815
 
0.1%
0.3704
 
0.1%
0.28470
 
0.1%
0.8441
 
0.1%
0.35378
 
< 0.1%
Other values (82)1631
 
0.2%
(Missing)744785
97.7%
ValueCountFrequency (%)
-502
 
< 0.1%
0.011
 
< 0.1%
0.023
 
< 0.1%
0.031
 
< 0.1%
0.049
< 0.1%
0.0510
< 0.1%
0.0615
< 0.1%
0.081
 
< 0.1%
0.11
 
< 0.1%
0.131
 
< 0.1%
ValueCountFrequency (%)
40001
 
< 0.1%
5.051
 
< 0.1%
216
 
< 0.1%
1.71
 
< 0.1%
1.41
 
< 0.1%
1.31
 
< 0.1%
1.26
 
< 0.1%
1.11
 
< 0.1%
12168
0.3%
0.981
 
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct87
Distinct (%)0.5%
Missing745037
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean7.371940677
Minimum6.71
Maximum7.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:36.292057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.71
5-th percentile7.22
Q17.32
median7.38
Q37.43
95-th percentile7.5
Maximum7.71
Range1
Interquartile range (IQR)0.11

Descriptive statistics

Standard deviation0.0872255322
Coefficient of variation (CV)0.01183209904
Kurtosis3.249979704
Mean7.371940677
Median Absolute Deviation (MAD)0.05
Skewness-0.9226287226
Sum125013.37
Variance0.007608293467
MonotonicityNot monotonic
2021-11-29T19:23:36.560460image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.381019
 
0.1%
7.4995
 
0.1%
7.36955
 
0.1%
7.42871
 
0.1%
7.39836
 
0.1%
7.34798
 
0.1%
7.37780
 
0.1%
7.41754
 
0.1%
7.35739
 
0.1%
7.44708
 
0.1%
Other values (77)8503
 
1.1%
(Missing)745037
97.8%
ValueCountFrequency (%)
6.711
< 0.1%
6.721
< 0.1%
6.731
< 0.1%
6.782
< 0.1%
6.812
< 0.1%
6.821
< 0.1%
6.842
< 0.1%
6.852
< 0.1%
6.872
< 0.1%
6.882
< 0.1%
ValueCountFrequency (%)
7.711
 
< 0.1%
7.692
 
< 0.1%
7.681
 
< 0.1%
7.642
 
< 0.1%
7.634
 
< 0.1%
7.628
 
< 0.1%
7.6114
< 0.1%
7.613
< 0.1%
7.5922
< 0.1%
7.5824
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct532
Distinct (%)3.1%
Missing744982
Missing (%)97.8%
Infinite0
Infinite (%)0.0%
Mean40.43427379
Minimum12
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:36.833627image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile28
Q134.7
median39
Q344
95-th percentile59
Maximum100
Range88
Interquartile range (IQR)9.3

Descriptive statistics

Standard deviation10.27561724
Coefficient of variation (CV)0.2541313663
Kurtosis6.256709119
Mean40.43427379
Median Absolute Deviation (MAD)5
Skewness1.868807446
Sum687908.3
Variance105.5883097
MonotonicityNot monotonic
2021-11-29T19:23:37.097420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38835
 
0.1%
36776
 
0.1%
40764
 
0.1%
39679
 
0.1%
34668
 
0.1%
42664
 
0.1%
35637
 
0.1%
37602
 
0.1%
41551
 
0.1%
44489
 
0.1%
Other values (522)10348
 
1.4%
(Missing)744982
97.8%
ValueCountFrequency (%)
121
 
< 0.1%
131
 
< 0.1%
157
 
< 0.1%
15.31
 
< 0.1%
168
 
< 0.1%
16.21
 
< 0.1%
16.42
 
< 0.1%
16.71
 
< 0.1%
1720
< 0.1%
17.91
 
< 0.1%
ValueCountFrequency (%)
1006
< 0.1%
995
< 0.1%
9811
< 0.1%
976
< 0.1%
963
 
< 0.1%
954
 
< 0.1%
945
< 0.1%
93.41
 
< 0.1%
936
< 0.1%
92.51
 
< 0.1%

SaO2
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct358
Distinct (%)2.5%
Missing747594
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean96.56646761
Minimum23
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:37.370798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile90.8
Q195.7
median97.5
Q398.7
95-th percentile99.6
Maximum100
Range77
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.729406437
Coefficient of variation (CV)0.03862009795
Kurtosis48.26623053
Mean96.56646761
Median Absolute Deviation (MAD)1.4
Skewness-4.922478481
Sum1390653.7
Variance13.90847238
MonotonicityNot monotonic
2021-11-29T19:23:37.637283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
98.8380
 
< 0.1%
99.2379
 
< 0.1%
99360
 
< 0.1%
98.7344
 
< 0.1%
98.6340
 
< 0.1%
99.1332
 
< 0.1%
98.9325
 
< 0.1%
99.4320
 
< 0.1%
98.3313
 
< 0.1%
98.5309
 
< 0.1%
Other values (348)10999
 
1.4%
(Missing)747594
98.1%
ValueCountFrequency (%)
231
< 0.1%
29.11
< 0.1%
36.61
< 0.1%
45.21
< 0.1%
50.31
< 0.1%
51.41
< 0.1%
52.51
< 0.1%
54.71
< 0.1%
56.61
< 0.1%
58.21
< 0.1%
ValueCountFrequency (%)
1007
 
< 0.1%
99.997
 
< 0.1%
99.851
 
< 0.1%
99.8241
< 0.1%
99.754
 
< 0.1%
99.7231
< 0.1%
99.651
 
< 0.1%
99.6254
< 0.1%
99.555
 
< 0.1%
99.5280
< 0.1%

AST
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1181
Distinct (%)8.8%
Missing748632
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean175.3223453
Minimum5
Maximum9961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:37.927620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile13
Q120
median32
Q372
95-th percentile651
Maximum9961
Range9956
Interquartile range (IQR)52

Descriptive statistics

Standard deviation658.974827
Coefficient of variation (CV)3.758647113
Kurtosis82.28943766
Mean175.3223453
Median Absolute Deviation (MAD)15
Skewness8.222250562
Sum2342832.5
Variance434247.8226
MonotonicityNot monotonic
2021-11-29T19:23:38.206093image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20424
 
0.1%
17416
 
0.1%
21411
 
0.1%
16396
 
0.1%
18394
 
0.1%
19391
 
0.1%
22369
 
< 0.1%
14336
 
< 0.1%
15331
 
< 0.1%
24328
 
< 0.1%
Other values (1171)9567
 
1.3%
(Missing)748632
98.2%
ValueCountFrequency (%)
59
 
< 0.1%
69
 
< 0.1%
711
 
< 0.1%
829
 
< 0.1%
955
 
< 0.1%
9.51
 
< 0.1%
1098
< 0.1%
11153
< 0.1%
12208
< 0.1%
13231
< 0.1%
ValueCountFrequency (%)
99611
< 0.1%
97471
< 0.1%
97101
< 0.1%
96021
< 0.1%
95821
< 0.1%
95201
< 0.1%
94891
< 0.1%
92441
< 0.1%
92291
< 0.1%
91851
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct235
Distinct (%)0.6%
Missing719903
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean23.25485841
Minimum1
Maximum268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:38.469482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q111
median17
Q328
95-th percentile63
Maximum268
Range267
Interquartile range (IQR)17

Descriptive statistics

Standard deviation19.72849602
Coefficient of variation (CV)0.8483601869
Kurtosis10.74457783
Mean23.25485841
Median Absolute Deviation (MAD)7
Skewness2.657516977
Sum978843.5
Variance389.2135553
MonotonicityNot monotonic
2021-11-29T19:23:38.741237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131993
 
0.3%
121953
 
0.3%
111940
 
0.3%
141913
 
0.3%
101822
 
0.2%
151799
 
0.2%
91646
 
0.2%
161629
 
0.2%
171599
 
0.2%
81470
 
0.2%
Other values (225)24328
 
3.2%
(Missing)719903
94.5%
ValueCountFrequency (%)
180
 
< 0.1%
1.52
 
< 0.1%
2110
 
< 0.1%
3290
 
< 0.1%
3.51
 
< 0.1%
4511
0.1%
4.53
 
< 0.1%
5728
0.1%
5.53
 
< 0.1%
6999
0.1%
ValueCountFrequency (%)
2681
< 0.1%
2521
< 0.1%
2321
< 0.1%
2271
< 0.1%
2111
< 0.1%
2071
< 0.1%
2031
< 0.1%
2022
< 0.1%
2011
< 0.1%
2001
< 0.1%

Alkalinephos
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct559
Distinct (%)4.2%
Missing748586
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean92.40454173
Minimum11
Maximum1650
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:39.005939image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile34
Q152
median70
Q3101
95-th percentile214.6
Maximum1650
Range1639
Interquartile range (IQR)49

Descriptive statistics

Standard deviation89.13203779
Coefficient of variation (CV)0.9645850315
Kurtosis62.40629615
Mean92.40454173
Median Absolute Deviation (MAD)21
Skewness6.252568515
Sum1239052.5
Variance7944.520161
MonotonicityNot monotonic
2021-11-29T19:23:39.265069image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58219
 
< 0.1%
56214
 
< 0.1%
61209
 
< 0.1%
54205
 
< 0.1%
57200
 
< 0.1%
53200
 
< 0.1%
60196
 
< 0.1%
51196
 
< 0.1%
52192
 
< 0.1%
49191
 
< 0.1%
Other values (549)11387
 
1.5%
(Missing)748586
98.2%
ValueCountFrequency (%)
112
 
< 0.1%
121
 
< 0.1%
132
 
< 0.1%
142
 
< 0.1%
155
 
< 0.1%
168
< 0.1%
177
< 0.1%
187
< 0.1%
1913
< 0.1%
2011
< 0.1%
ValueCountFrequency (%)
16503
< 0.1%
14471
 
< 0.1%
13661
 
< 0.1%
12761
 
< 0.1%
12211
 
< 0.1%
12141
 
< 0.1%
11601
 
< 0.1%
11341
 
< 0.1%
11291
 
< 0.1%
11161
 
< 0.1%

Calcium
Real number (ℝ≥0)

MISSING

Distinct533
Distinct (%)1.0%
Missing709982
Missing (%)93.2%
Infinite0
Infinite (%)0.0%
Mean6.983445485
Minimum1
Maximum27.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:39.732961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.13
Q17.2
median8.2
Q38.7
95-th percentile9.5
Maximum27.9
Range26.9
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation3.020360083
Coefficient of variation (CV)0.4325028512
Kurtosis0.582637215
Mean6.983445485
Median Absolute Deviation (MAD)0.6
Skewness-1.001488168
Sum363229.95
Variance9.122575033
MonotonicityNot monotonic
2021-11-29T19:23:40.010646image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.32538
 
0.3%
8.52521
 
0.3%
8.62508
 
0.3%
8.42461
 
0.3%
8.22416
 
0.3%
8.72288
 
0.3%
8.12210
 
0.3%
8.82175
 
0.3%
81977
 
0.3%
8.91911
 
0.3%
Other values (523)29008
 
3.8%
(Missing)709982
93.2%
ValueCountFrequency (%)
157
 
< 0.1%
1.0174
 
< 0.1%
1.0287
 
< 0.1%
1.0395
 
< 0.1%
1.04127
< 0.1%
1.05129
< 0.1%
1.06173
< 0.1%
1.07178
< 0.1%
1.08235
< 0.1%
1.09283
< 0.1%
ValueCountFrequency (%)
27.91
< 0.1%
272
< 0.1%
25.21
< 0.1%
24.91
< 0.1%
23.71
< 0.1%
22.61
< 0.1%
22.22
< 0.1%
21.21
< 0.1%
20.61
< 0.1%
20.42
< 0.1%

Chloride
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)1.5%
Missing757306
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean106.7095329
Minimum74
Maximum124
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:40.288551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile99
Q1104
median107
Q3110
95-th percentile114
Maximum124
Range50
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.887926633
Coefficient of variation (CV)0.0458059041
Kurtosis3.039882422
Mean106.7095329
Median Absolute Deviation (MAD)3
Skewness-0.7408788256
Sum500361
Variance23.89182677
MonotonicityNot monotonic
2021-11-29T19:23:40.552413image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
107449
 
0.1%
106446
 
0.1%
108436
 
0.1%
105389
 
0.1%
109380
 
< 0.1%
110303
 
< 0.1%
104290
 
< 0.1%
111258
 
< 0.1%
103233
 
< 0.1%
112196
 
< 0.1%
Other values (61)1309
 
0.2%
(Missing)757306
99.4%
ValueCountFrequency (%)
741
 
< 0.1%
781
 
< 0.1%
801
 
< 0.1%
811
 
< 0.1%
821
 
< 0.1%
832
 
< 0.1%
852
 
< 0.1%
869
< 0.1%
873
 
< 0.1%
8810
< 0.1%
ValueCountFrequency (%)
1247
 
< 0.1%
1233
 
< 0.1%
1225
 
< 0.1%
1215
 
< 0.1%
120.51
 
< 0.1%
1208
 
< 0.1%
1196
 
< 0.1%
11818
< 0.1%
117.51
 
< 0.1%
11720
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1382
Distinct (%)3.3%
Missing719866
Missing (%)94.5%
Infinite0
Infinite (%)0.0%
Mean1.643156258
Minimum0.2
Maximum41.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:40.819421image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.52
Q10.75
median0.99
Q31.51
95-th percentile5.66
Maximum41.9
Range41.7
Interquartile range (IQR)0.76

Descriptive statistics

Standard deviation2.093640019
Coefficient of variation (CV)1.27415759
Kurtosis28.12459439
Mean1.643156258
Median Absolute Deviation (MAD)0.31
Skewness4.484662436
Sum69224.53
Variance4.383328528
MonotonicityNot monotonic
2021-11-29T19:23:41.072630image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.82519
 
0.1%
0.8515
 
0.1%
0.77514
 
0.1%
0.81511
 
0.1%
0.79500
 
0.1%
0.73482
 
0.1%
0.69479
 
0.1%
0.84476
 
0.1%
0.78474
 
0.1%
0.68474
 
0.1%
Other values (1372)37185
 
4.9%
(Missing)719866
94.5%
ValueCountFrequency (%)
0.27
< 0.1%
0.212
 
< 0.1%
0.222
 
< 0.1%
0.231
 
< 0.1%
0.241
 
< 0.1%
0.252
 
< 0.1%
0.261
 
< 0.1%
0.274
< 0.1%
0.285
< 0.1%
0.294
< 0.1%
ValueCountFrequency (%)
41.91
 
< 0.1%
29.861
 
< 0.1%
29.21
 
< 0.1%
255
< 0.1%
24.991
 
< 0.1%
24.031
 
< 0.1%
241
 
< 0.1%
23.831
 
< 0.1%
23.711
 
< 0.1%
23.651
 
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct212
Distinct (%)11.7%
Missing760187
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1.000647124
Minimum0.01
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:41.331753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1
Q10.1
median0.2
Q30.6825
95-th percentile4.1
Maximum30
Range29.99
Interquartile range (IQR)0.5825

Descriptive statistics

Standard deviation2.605067509
Coefficient of variation (CV)2.603382798
Kurtosis37.50731418
Mean1.000647124
Median Absolute Deviation (MAD)0.1
Skewness5.623408414
Sum1809.17
Variance6.786376725
MonotonicityNot monotonic
2021-11-29T19:23:41.592886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1485
 
0.1%
0.2306
 
< 0.1%
0.3139
 
< 0.1%
0.4102
 
< 0.1%
0.549
 
< 0.1%
0.645
 
< 0.1%
132
 
< 0.1%
0.730
 
< 0.1%
0.820
 
< 0.1%
1.120
 
< 0.1%
Other values (202)580
 
0.1%
(Missing)760187
99.8%
ValueCountFrequency (%)
0.018
 
< 0.1%
0.024
 
< 0.1%
0.035
 
< 0.1%
0.044
 
< 0.1%
0.056
 
< 0.1%
0.066
 
< 0.1%
0.078
 
< 0.1%
0.084
 
< 0.1%
0.0913
 
< 0.1%
0.1485
0.1%
ValueCountFrequency (%)
301
< 0.1%
23.921
< 0.1%
23.621
< 0.1%
22.681
< 0.1%
20.571
< 0.1%
20.551
< 0.1%
202
< 0.1%
19.541
< 0.1%
19.31
< 0.1%
19.081
< 0.1%

Glucose
Real number (ℝ≥0)

MISSING

Distinct1012
Distinct (%)0.6%
Missing593135
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean138.8344149
Minimum13
Maximum891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:41.868959image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile83
Q1108
median128
Q3155
95-th percentile236
Maximum891
Range878
Interquartile range (IQR)47

Descriptive statistics

Standard deviation51.05680343
Coefficient of variation (CV)0.3677532222
Kurtosis10.06188752
Mean138.8344149
Median Absolute Deviation (MAD)23
Skewness2.320803976
Sum23443579.3
Variance2606.797177
MonotonicityNot monotonic
2021-11-29T19:23:42.129447image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1202102
 
0.3%
1142073
 
0.3%
1182069
 
0.3%
1152044
 
0.3%
1162042
 
0.3%
1212028
 
0.3%
1172022
 
0.3%
1122021
 
0.3%
1242003
 
0.3%
1222003
 
0.3%
Other values (1002)148453
 
19.5%
(Missing)593135
77.8%
ValueCountFrequency (%)
131
 
< 0.1%
151
 
< 0.1%
161
 
< 0.1%
211
 
< 0.1%
23.51
 
< 0.1%
261
 
< 0.1%
282
 
< 0.1%
29.51
 
< 0.1%
3031
< 0.1%
30.51
 
< 0.1%
ValueCountFrequency (%)
8911
< 0.1%
8711
< 0.1%
8501
< 0.1%
7881
< 0.1%
7571
< 0.1%
7341
< 0.1%
7221
< 0.1%
7081
< 0.1%
6931
< 0.1%
6921
< 0.1%

Lactate
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct1244
Distinct (%)8.7%
Missing747692
Missing (%)98.1%
Infinite0
Infinite (%)0.0%
Mean2.983440537
Minimum0.4
Maximum22.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:42.408577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.4
5-th percentile0.86
Q11.33
median1.97
Q33.43
95-th percentile8.728
Maximum22.25
Range21.85
Interquartile range (IQR)2.1

Descriptive statistics

Standard deviation2.833046924
Coefficient of variation (CV)0.9495905445
Kurtosis9.120187485
Mean2.983440537
Median Absolute Deviation (MAD)0.8
Skewness2.730254966
Sum42672.15
Variance8.026154873
MonotonicityNot monotonic
2021-11-29T19:23:42.668773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.2139
 
< 0.1%
1.1133
 
< 0.1%
1.3129
 
< 0.1%
1.4123
 
< 0.1%
1117
 
< 0.1%
0.8113
 
< 0.1%
1.7100
 
< 0.1%
0.997
 
< 0.1%
1.687
 
< 0.1%
1.3181
 
< 0.1%
Other values (1234)13184
 
1.7%
(Missing)747692
98.1%
ValueCountFrequency (%)
0.41
 
< 0.1%
0.461
 
< 0.1%
0.512
< 0.1%
0.533
 
< 0.1%
0.542
 
< 0.1%
0.552
 
< 0.1%
0.564
 
< 0.1%
0.574
 
< 0.1%
0.581
 
< 0.1%
0.592
 
< 0.1%
ValueCountFrequency (%)
22.257
< 0.1%
21.541
 
< 0.1%
21.521
 
< 0.1%
21.261
 
< 0.1%
21.211
 
< 0.1%
20.941
 
< 0.1%
20.371
 
< 0.1%
19.791
 
< 0.1%
19.712
 
< 0.1%
19.661
 
< 0.1%

Magnesium
Real number (ℝ≥0)

MISSING

Distinct90
Distinct (%)0.2%
Missing725525
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean2.069060872
Minimum0.5
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:42.929063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.5
Q11.8
median2
Q32.2
95-th percentile2.7
Maximum9.8
Range9.3
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.4102271075
Coefficient of variation (CV)0.1982672975
Kurtosis26.81203344
Mean2.069060872
Median Absolute Deviation (MAD)0.2
Skewness2.817684465
Sum75458.65
Variance0.1682862797
MonotonicityNot monotonic
2021-11-29T19:23:43.189063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25224
 
0.7%
1.94760
 
0.6%
2.14700
 
0.6%
2.23771
 
0.5%
1.83637
 
0.5%
2.32707
 
0.4%
1.72361
 
0.3%
2.41845
 
0.2%
1.61492
 
0.2%
2.51247
 
0.2%
Other values (80)4726
 
0.6%
(Missing)725525
95.2%
ValueCountFrequency (%)
0.52
 
< 0.1%
0.61
 
< 0.1%
0.72
 
< 0.1%
0.86
 
< 0.1%
0.916
 
< 0.1%
142
 
< 0.1%
1.171
 
< 0.1%
1.2137
< 0.1%
1.3274
< 0.1%
1.351
 
< 0.1%
ValueCountFrequency (%)
9.81
< 0.1%
9.31
< 0.1%
9.21
< 0.1%
9.11
< 0.1%
8.41
< 0.1%
8.11
< 0.1%
7.91
< 0.1%
7.61
< 0.1%
7.11
< 0.1%
72
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct158
Distinct (%)0.7%
Missing739590
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean3.46529123
Minimum0.6
Maximum15.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:43.649141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile1.7
Q12.6
median3.3
Q34
95-th percentile6
Maximum15.5
Range14.9
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation1.379108771
Coefficient of variation (CV)0.3979777398
Kurtosis5.242778417
Mean3.46529123
Median Absolute Deviation (MAD)0.7
Skewness1.578399678
Sum77639.85
Variance1.901941003
MonotonicityNot monotonic
2021-11-29T19:23:43.911842image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3877
 
0.1%
3.4862
 
0.1%
2.9855
 
0.1%
3.2850
 
0.1%
3.5821
 
0.1%
2.8817
 
0.1%
3811
 
0.1%
3.1805
 
0.1%
3.6749
 
0.1%
2.7737
 
0.1%
Other values (148)14221
 
1.9%
(Missing)739590
97.1%
ValueCountFrequency (%)
0.628
 
< 0.1%
0.720
 
< 0.1%
0.751
 
< 0.1%
0.839
 
< 0.1%
0.851
 
< 0.1%
0.925
 
< 0.1%
1111
< 0.1%
1.162
< 0.1%
1.286
< 0.1%
1.3117
< 0.1%
ValueCountFrequency (%)
15.51
 
< 0.1%
14.21
 
< 0.1%
12.71
 
< 0.1%
12.61
 
< 0.1%
12.22
 
< 0.1%
1222
< 0.1%
11.82
 
< 0.1%
11.72
 
< 0.1%
11.64
 
< 0.1%
11.51
 
< 0.1%

Potassium
Real number (ℝ≥0)

MISSING

Distinct391
Distinct (%)0.7%
Missing703306
Missing (%)92.3%
Infinite0
Infinite (%)0.0%
Mean4.097531905
Minimum1.3
Maximum15.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:44.182808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.3
5-th percentile3.2
Q13.7
median4
Q34.4
95-th percentile5.2
Maximum15.8
Range14.5
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.6538478846
Coefficient of variation (CV)0.1595711515
Kurtosis9.95534929
Mean4.097531905
Median Absolute Deviation (MAD)0.3
Skewness1.68795451
Sum240480.05
Variance0.4275170562
MonotonicityNot monotonic
2021-11-29T19:23:44.441649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44464
 
0.6%
3.94404
 
0.6%
3.84249
 
0.6%
4.14068
 
0.5%
3.73719
 
0.5%
4.23651
 
0.5%
3.63250
 
0.4%
4.33080
 
0.4%
4.42721
 
0.4%
3.52446
 
0.3%
Other values (381)22637
 
3.0%
(Missing)703306
92.3%
ValueCountFrequency (%)
1.33
 
< 0.1%
1.43
 
< 0.1%
1.451
 
< 0.1%
1.52
 
< 0.1%
1.73
 
< 0.1%
1.81
 
< 0.1%
1.95
 
< 0.1%
28
 
< 0.1%
2.110
< 0.1%
2.220
< 0.1%
ValueCountFrequency (%)
15.81
 
< 0.1%
11.81
 
< 0.1%
11.52
< 0.1%
10.82
< 0.1%
10.751
 
< 0.1%
10.63
< 0.1%
10.42
< 0.1%
10.21
 
< 0.1%
101
 
< 0.1%
9.84
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct305
Distinct (%)2.3%
Missing748547
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean1.695761452
Minimum0.1
Maximum49.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:44.719883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.6
median0.8
Q31.4
95-th percentile5.1
Maximum49.6
Range49.5
Interquartile range (IQR)0.8

Descriptive statistics

Standard deviation3.42913138
Coefficient of variation (CV)2.022177929
Kurtosis53.37953927
Mean1.695761452
Median Absolute Deviation (MAD)0.3
Skewness6.513752117
Sum22804.6
Variance11.75894202
MonotonicityNot monotonic
2021-11-29T19:23:45.004190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.61292
 
0.2%
0.51257
 
0.2%
0.71214
 
0.2%
0.41064
 
0.1%
0.81045
 
0.1%
0.9857
 
0.1%
1738
 
0.1%
0.3628
 
0.1%
1.1585
 
0.1%
1.2457
 
0.1%
Other values (295)4311
 
0.6%
(Missing)748547
98.2%
ValueCountFrequency (%)
0.159
 
< 0.1%
0.151
 
< 0.1%
0.2236
 
< 0.1%
0.252
 
< 0.1%
0.3628
0.1%
0.352
 
< 0.1%
0.41064
0.1%
0.452
 
< 0.1%
0.51257
0.2%
0.552
 
< 0.1%
ValueCountFrequency (%)
49.62
< 0.1%
49.21
< 0.1%
46.41
< 0.1%
45.31
< 0.1%
44.51
< 0.1%
43.31
< 0.1%
42.91
< 0.1%
42.81
< 0.1%
40.91
< 0.1%
40.32
< 0.1%

TroponinI
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2300
Distinct (%)16.6%
Missing748179
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean8.220386508
Minimum0.01
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:45.281343image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.03
median0.22
Q33.1125
95-th percentile40
Maximum440
Range439.99
Interquartile range (IQR)3.0825

Descriptive statistics

Standard deviation25.47879536
Coefficient of variation (CV)3.099464402
Kurtosis56.61605229
Mean8.220386508
Median Absolute Deviation (MAD)0.21
Skewness6.308549685
Sum113572.86
Variance649.1690128
MonotonicityNot monotonic
2021-11-29T19:23:45.540854image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011788
 
0.2%
0.031242
 
0.2%
0.02508
 
0.1%
0.04469
 
0.1%
0.05369
 
< 0.1%
0.06348
 
< 0.1%
0.07292
 
< 0.1%
40252
 
< 0.1%
0.08246
 
< 0.1%
0.1208
 
< 0.1%
Other values (2290)8094
 
1.1%
(Missing)748179
98.2%
ValueCountFrequency (%)
0.011788
0.2%
0.02508
 
0.1%
0.031242
0.2%
0.04469
 
0.1%
0.05369
 
< 0.1%
0.06348
 
< 0.1%
0.07292
 
< 0.1%
0.08246
 
< 0.1%
0.09205
 
< 0.1%
0.1208
 
< 0.1%
ValueCountFrequency (%)
4403
< 0.1%
394.031
 
< 0.1%
381.61
 
< 0.1%
349.051
 
< 0.1%
338.921
 
< 0.1%
325.311
 
< 0.1%
271.61
 
< 0.1%
255.181
 
< 0.1%
243.811
 
< 0.1%
235.881
 
< 0.1%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct521
Distinct (%)1.2%
Missing717620
Missing (%)94.2%
Infinite0
Infinite (%)0.0%
Mean31.04406152
Minimum9.1
Maximum70.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:45.800354image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum9.1
5-th percentile21.3
Q126
median30.5
Q335.7
95-th percentile42.3
Maximum70.2
Range61.1
Interquartile range (IQR)9.7

Descriptive statistics

Standard deviation6.594168851
Coefficient of variation (CV)0.212413213
Kurtosis-0.1709400975
Mean31.04406152
Median Absolute Deviation (MAD)4.8
Skewness0.3392415005
Sum1377580.23
Variance43.48306284
MonotonicityNot monotonic
2021-11-29T19:23:46.056325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27342
 
< 0.1%
29340
 
< 0.1%
26322
 
< 0.1%
28312
 
< 0.1%
24307
 
< 0.1%
25298
 
< 0.1%
33297
 
< 0.1%
30289
 
< 0.1%
34287
 
< 0.1%
29.1282
 
< 0.1%
Other values (511)41299
 
5.4%
(Missing)717620
94.2%
ValueCountFrequency (%)
9.11
< 0.1%
9.31
< 0.1%
9.61
< 0.1%
10.71
< 0.1%
10.81
< 0.1%
10.91
< 0.1%
11.31
< 0.1%
11.51
< 0.1%
11.61
< 0.1%
12.41
< 0.1%
ValueCountFrequency (%)
70.21
 
< 0.1%
653
< 0.1%
64.11
 
< 0.1%
63.41
 
< 0.1%
63.21
 
< 0.1%
621
 
< 0.1%
61.21
 
< 0.1%
60.21
 
< 0.1%
59.81
 
< 0.1%
59.41
 
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct269
Distinct (%)0.6%
Missing717225
Missing (%)94.1%
Infinite0
Infinite (%)0.0%
Mean10.19503641
Minimum2.3
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:46.324126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.3
5-th percentile7.1
Q18.5
median9.9
Q311.7
95-th percentile14.2
Maximum30
Range27.7
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation2.252607625
Coefficient of variation (CV)0.2209514057
Kurtosis0.6523609656
Mean10.19503641
Median Absolute Deviation (MAD)1.6
Skewness0.6047575824
Sum456431.78
Variance5.074241113
MonotonicityNot monotonic
2021-11-29T19:23:46.574557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.5855
 
0.1%
9.1827
 
0.1%
9816
 
0.1%
8.6808
 
0.1%
8.7805
 
0.1%
8.4799
 
0.1%
9.2798
 
0.1%
9.3774
 
0.1%
9.4766
 
0.1%
8.8764
 
0.1%
Other values (259)36758
 
4.8%
(Missing)717225
94.1%
ValueCountFrequency (%)
2.31
 
< 0.1%
2.61
 
< 0.1%
2.81
 
< 0.1%
2.91
 
< 0.1%
31
 
< 0.1%
3.63
< 0.1%
3.72
< 0.1%
3.83
< 0.1%
3.91
 
< 0.1%
43
< 0.1%
ValueCountFrequency (%)
301
 
< 0.1%
26.61
 
< 0.1%
251
 
< 0.1%
24.82
< 0.1%
241
 
< 0.1%
23.82
< 0.1%
23.63
< 0.1%
23.42
< 0.1%
23.21
 
< 0.1%
22.41
 
< 0.1%

PTT
Real number (ℝ≥0)

MISSING

Distinct920
Distinct (%)12.4%
Missing754602
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean43.55896794
Minimum20
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:46.830062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile24.2
Q128.5
median32.3
Q342
95-th percentile99.54
Maximum250
Range230
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation35.59428496
Coefficient of variation (CV)0.8171517058
Kurtosis18.49122077
Mean43.55896794
Median Absolute Deviation (MAD)5
Skewness4.077628816
Sum322031.45
Variance1266.953122
MonotonicityNot monotonic
2021-11-29T19:23:47.113964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24981
 
< 0.1%
30.869
 
< 0.1%
29.661
 
< 0.1%
30.759
 
< 0.1%
30.459
 
< 0.1%
2859
 
< 0.1%
29.758
 
< 0.1%
31.356
 
< 0.1%
27.456
 
< 0.1%
3055
 
< 0.1%
Other values (910)6780
 
0.9%
(Missing)754602
99.0%
ValueCountFrequency (%)
2038
< 0.1%
20.16
 
< 0.1%
20.32
 
< 0.1%
20.44
 
< 0.1%
20.53
 
< 0.1%
20.64
 
< 0.1%
20.71
 
< 0.1%
20.83
 
< 0.1%
20.98
 
< 0.1%
214
 
< 0.1%
ValueCountFrequency (%)
25011
 
< 0.1%
249.915
 
< 0.1%
24981
< 0.1%
248.71
 
< 0.1%
2481
 
< 0.1%
247.51
 
< 0.1%
2473
 
< 0.1%
246.81
 
< 0.1%
242.61
 
< 0.1%
238.11
 
< 0.1%

WBC
Real number (ℝ≥0)

MISSING

Distinct608
Distinct (%)1.5%
Missing721896
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean10.72089279
Minimum0.1
Maximum440
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:47.590210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.3
Q17
median9.6
Q312.8
95-th percentile20
Maximum440
Range439.9
Interquartile range (IQR)5.8

Descriptive statistics

Standard deviation7.918226524
Coefficient of variation (CV)0.7385790231
Kurtosis600.6686565
Mean10.72089279
Median Absolute Deviation (MAD)2.8
Skewness16.86507984
Sum429897.08
Variance62.69831128
MonotonicityNot monotonic
2021-11-29T19:23:47.854353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.6475
 
0.1%
7.8458
 
0.1%
8456
 
0.1%
7.4448
 
0.1%
8.8446
 
0.1%
8.2442
 
0.1%
7.6439
 
0.1%
8.4427
 
0.1%
10427
 
0.1%
7.2422
 
0.1%
Other values (598)35659
 
4.7%
(Missing)721896
94.7%
ValueCountFrequency (%)
0.128
< 0.1%
0.210
 
< 0.1%
0.35
 
< 0.1%
0.48
 
< 0.1%
0.53
 
< 0.1%
0.68
 
< 0.1%
0.75
 
< 0.1%
0.87
 
< 0.1%
0.98
 
< 0.1%
18
 
< 0.1%
ValueCountFrequency (%)
4401
< 0.1%
3871
< 0.1%
317.91
< 0.1%
3021
< 0.1%
296.11
< 0.1%
2511
< 0.1%
215.31
< 0.1%
199.21
< 0.1%
182.61
< 0.1%
180.51
< 0.1%

Fibrinogen
Real number (ℝ≥0)

MISSING

Distinct637
Distinct (%)15.1%
Missing757783
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean280.4195157
Minimum35
Maximum1179
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:48.118612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile107.55
Q1183
median251
Q3341
95-th percentile562.9
Maximum1179
Range1144
Interquartile range (IQR)158

Descriptive statistics

Standard deviation144.2962929
Coefficient of variation (CV)0.5145729339
Kurtosis3.635724739
Mean280.4195157
Median Absolute Deviation (MAD)76
Skewness1.546856177
Sum1181127
Variance20821.42014
MonotonicityNot monotonic
2021-11-29T19:23:48.391125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21733
 
< 0.1%
20029
 
< 0.1%
23025
 
< 0.1%
24825
 
< 0.1%
21925
 
< 0.1%
27223
 
< 0.1%
15123
 
< 0.1%
22923
 
< 0.1%
15221
 
< 0.1%
20821
 
< 0.1%
Other values (627)3964
 
0.5%
(Missing)757783
99.4%
ValueCountFrequency (%)
3516
< 0.1%
411
 
< 0.1%
423
 
< 0.1%
463
 
< 0.1%
482
 
< 0.1%
501
 
< 0.1%
512
 
< 0.1%
525
 
< 0.1%
532
 
< 0.1%
571
 
< 0.1%
ValueCountFrequency (%)
11791
 
< 0.1%
10008
< 0.1%
9661
 
< 0.1%
9542
 
< 0.1%
9451
 
< 0.1%
9321
 
< 0.1%
9191
 
< 0.1%
9121
 
< 0.1%
9013
 
< 0.1%
8971
 
< 0.1%

Platelets
Real number (ℝ≥0)

MISSING

Distinct758
Distinct (%)1.9%
Missing721285
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean191.4548637
Minimum1
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:48.658642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile63
Q1126
median180
Q3240
95-th percentile359
Maximum2322
Range2321
Interquartile range (IQR)114

Descriptive statistics

Standard deviation95.87961665
Coefficient of variation (CV)0.5007948861
Kurtosis10.02842462
Mean191.4548637
Median Absolute Deviation (MAD)57
Skewness1.536460392
Sum7794127.5
Variance9192.90089
MonotonicityNot monotonic
2021-11-29T19:23:48.917816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167234
 
< 0.1%
162220
 
< 0.1%
141218
 
< 0.1%
175215
 
< 0.1%
166209
 
< 0.1%
152208
 
< 0.1%
149208
 
< 0.1%
151208
 
< 0.1%
183205
 
< 0.1%
163205
 
< 0.1%
Other values (748)38580
 
5.1%
(Missing)721285
94.7%
ValueCountFrequency (%)
11
 
< 0.1%
25
< 0.1%
34
< 0.1%
47
< 0.1%
55
< 0.1%
64
< 0.1%
73
 
< 0.1%
85
< 0.1%
98
< 0.1%
105
< 0.1%
ValueCountFrequency (%)
23221
< 0.1%
11401
< 0.1%
10361
< 0.1%
10081
< 0.1%
9841
< 0.1%
9651
< 0.1%
9321
< 0.1%
9201
< 0.1%
9091
< 0.1%
9071
< 0.1%

Age
Real number (ℝ≥0)

Distinct77
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.96485279
Minimum14
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:49.184886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile30
Q150
median63
Q372
95-th percentile85
Maximum100
Range86
Interquartile range (IQR)22

Descriptive statistics

Standard deviation16.57960365
Coefficient of variation (CV)0.2719534763
Kurtosis-0.1167287965
Mean60.96485279
Median Absolute Deviation (MAD)11
Skewness-0.2954254824
Sum46454913
Variance274.8832572
MonotonicityNot monotonic
2021-11-29T19:23:49.459635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6721627
 
2.8%
6821545
 
2.8%
6520543
 
2.7%
7120260
 
2.7%
6619737
 
2.6%
6118930
 
2.5%
6918877
 
2.5%
6218740
 
2.5%
7318581
 
2.4%
7017875
 
2.3%
Other values (67)565280
74.2%
ValueCountFrequency (%)
1437
 
< 0.1%
1577
 
< 0.1%
16210
 
< 0.1%
17425
 
0.1%
181260
 
0.2%
191773
0.2%
202569
0.3%
213542
0.5%
222316
0.3%
232857
0.4%
ValueCountFrequency (%)
10014978
2.0%
894539
 
0.6%
884944
 
0.6%
875503
 
0.7%
867002
0.9%
856877
0.9%
847973
1.0%
839449
1.2%
829708
1.3%
818439
1.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 MiB
1
411579 
0
350416 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters761995
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Length

2021-11-29T19:23:49.721761image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:23:49.874971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Most occurring characters

ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number761995
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Most occurring scripts

ValueCountFrequency (%)
Common761995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII761995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1411579
54.0%
0350416
46.0%

Unit1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing225795
Missing (%)29.6%
Memory size5.8 MiB
0.0
274193 
1.0
262007 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1608600
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.0274193
36.0%
1.0262007
34.4%
(Missing)225795
29.6%

Length

2021-11-29T19:23:50.002573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:23:50.144473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.0274193
51.1%
1.0262007
48.9%

Most occurring characters

ValueCountFrequency (%)
0810393
50.4%
.536200
33.3%
1262007
 
16.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1072400
66.7%
Other Punctuation536200
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0810393
75.6%
1262007
 
24.4%
Other Punctuation
ValueCountFrequency (%)
.536200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1608600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0810393
50.4%
.536200
33.3%
1262007
 
16.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1608600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0810393
50.4%
.536200
33.3%
1262007
 
16.3%

Unit2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing225795
Missing (%)29.6%
Memory size5.8 MiB
1.0
274193 
0.0
262007 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1608600
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.0274193
36.0%
0.0262007
34.4%
(Missing)225795
29.6%

Length

2021-11-29T19:23:50.274009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:23:50.415726image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.0274193
51.1%
0.0262007
48.9%

Most occurring characters

ValueCountFrequency (%)
0798207
49.6%
.536200
33.3%
1274193
 
17.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1072400
66.7%
Other Punctuation536200
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0798207
74.4%
1274193
 
25.6%
Other Punctuation
ValueCountFrequency (%)
.536200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1608600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0798207
49.6%
.536200
33.3%
1274193
 
17.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1608600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0798207
49.6%
.536200
33.3%
1274193
 
17.0%

HospAdmTime
Real number (ℝ)

ZEROS

Distinct7975
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-60.37626075
Minimum-5366.86
Maximum0
Zeros49742
Zeros (%)6.5%
Negative712253
Negative (%)93.5%
Memory size5.8 MiB
2021-11-29T19:23:50.559074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-5366.86
5-th percentile-266.6
Q1-56.16
median-8.95
Q3-3.1
95-th percentile0
Maximum0
Range5366.86
Interquartile range (IQR)53.06

Descriptive statistics

Standard deviation168.5246272
Coefficient of variation (CV)-2.791239886
Kurtosis383.5293822
Mean-60.37626075
Median Absolute Deviation (MAD)8.92
Skewness-14.87989159
Sum-46006408.81
Variance28400.54996
MonotonicityNot monotonic
2021-11-29T19:23:50.837861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
049742
 
6.5%
-0.0210227
 
1.3%
-0.039086
 
1.2%
-0.018130
 
1.1%
-0.046025
 
0.8%
-0.055521
 
0.7%
-0.064652
 
0.6%
-0.074005
 
0.5%
-0.093309
 
0.4%
-0.082935
 
0.4%
Other values (7965)658363
86.4%
ValueCountFrequency (%)
-5366.86260
< 0.1%
-3397.6436
 
< 0.1%
-3342.3441
 
< 0.1%
-3189.3932
 
< 0.1%
-3112.1212
 
< 0.1%
-2929.3744
 
< 0.1%
-2842.1112
 
< 0.1%
-2667.3421
 
< 0.1%
-2384.7829
 
< 0.1%
-2382.3436
 
< 0.1%
ValueCountFrequency (%)
049742
6.5%
-0.018130
 
1.1%
-0.0210227
 
1.3%
-0.039086
 
1.2%
-0.046025
 
0.8%
-0.055521
 
0.7%
-0.064652
 
0.6%
-0.074005
 
0.5%
-0.082935
 
0.4%
-0.093309
 
0.4%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct336
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.78392903
Minimum1
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:51.308247image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q110
median20
Q334
95-th percentile64
Maximum336
Range335
Interquartile range (IQR)24

Descriptive statistics

Standard deviation29.82513066
Coefficient of variation (CV)1.113545762
Kurtosis24.64936027
Mean26.78392903
Median Absolute Deviation (MAD)11
Skewness4.159841885
Sum20409220
Variance889.5384189
MonotonicityNot monotonic
2021-11-29T19:23:51.581655image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
819980
 
2.6%
719966
 
2.6%
619941
 
2.6%
519887
 
2.6%
419810
 
2.6%
919794
 
2.6%
1019692
 
2.6%
319664
 
2.6%
1119578
 
2.6%
1219468
 
2.6%
Other values (326)564215
74.0%
ValueCountFrequency (%)
118704
2.5%
219445
2.6%
319664
2.6%
419810
2.6%
519887
2.6%
619941
2.6%
719966
2.6%
819980
2.6%
919794
2.6%
1019692
2.6%
ValueCountFrequency (%)
3367
< 0.1%
3358
< 0.1%
3349
< 0.1%
3339
< 0.1%
3329
< 0.1%
3319
< 0.1%
3309
< 0.1%
3299
< 0.1%
3289
< 0.1%
32710
< 0.1%

SepsisLabel
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 MiB
0
751215 
1
 
10780

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters761995
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Length

2021-11-29T19:23:51.859484image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:23:52.012003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number761995
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Common761995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII761995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0751215
98.6%
110780
 
1.4%

Sepsis
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 MiB
0
694549 
1
 
67446

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters761995
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Length

2021-11-29T19:23:52.149766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:23:52.302672image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number761995
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
Common761995
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII761995
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0694549
91.1%
167446
 
8.9%

Hours
Real number (ℝ≥0)

HIGH CORRELATION

Distinct230
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.3179614
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.8 MiB
2021-11-29T19:23:52.449322image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile19
Q136
median44
Q352
95-th percentile139
Maximum336
Range328
Interquartile range (IQR)16

Descriptive statistics

Standard deviation44.52602971
Coefficient of variation (CV)0.8510658389
Kurtosis16.56059538
Mean52.3179614
Median Absolute Deviation (MAD)8
Skewness3.821416747
Sum39866025
Variance1982.567322
MonotonicityNot monotonic
2021-11-29T19:23:52.716063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3927183
 
3.6%
4326230
 
3.4%
4126199
 
3.4%
4026040
 
3.4%
3825346
 
3.3%
4225032
 
3.3%
4424772
 
3.3%
4724064
 
3.2%
4523940
 
3.1%
3623904
 
3.1%
Other values (220)509285
66.8%
ValueCountFrequency (%)
81632
 
0.2%
91026
 
0.1%
101260
 
0.2%
111320
 
0.2%
121968
 
0.3%
132665
0.3%
143052
0.4%
154575
0.6%
165232
0.7%
176341
0.8%
ValueCountFrequency (%)
3361680
0.2%
335670
 
0.1%
334334
 
< 0.1%
333333
 
< 0.1%
327327
 
< 0.1%
326326
 
< 0.1%
320320
 
< 0.1%
318318
 
< 0.1%
312624
 
0.1%
310620
 
0.1%

Interactions

2021-11-29T19:23:07.722477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:55.999807image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:56.454151image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:56.860710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:57.279731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:57.589073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:57.966080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:58.323965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:58.681171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:59.026927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:59.262175image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:59.509227image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:22:59.939834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:00.178657image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:00.435713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:00.672528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:00.908636image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:01.165434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:01.415584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:01.667266image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:01.934443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:02.171041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:02.416349image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:02.649475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:02.933649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:03.172394image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:03.414190image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:03.652356image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:03.925827image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:04.180968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:04.423466image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:04.669026image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:04.920235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:05.155399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:05.397578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:05.824547image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:06.083552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:06.500242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:06.903619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:23:07.314390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T19:23:53.055143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T19:23:53.856256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T19:23:54.654680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T19:23:55.333090image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T19:23:08.301439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T19:23:13.193189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T19:23:24.291843image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T19:23:27.114707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDlevel_1HRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
01000010NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6410024
1100001193.092.5NaN110.076.056.022.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6420024
2100001291.096.0NaN108.084.572.023.5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN233.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6430024
3100001393.098.0NaN123.087.061.021.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6440024
4100001493.095.0NaN110.081.070.020.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6450024
51000015NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6460024
6100001691.597.036.5104.075.060.020.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6470024
7100001794.095.0NaN114.085.066.020.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN154.0NaN2.1NaN3.7NaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6480024
8100001894.095.0NaN121.088.069.020.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.6490024
91000019102.095.0NaN117.089.070.020.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN7311.00.0-214.64100024

Last rows

PatientIDlevel_1HRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
7619851200002572.098.036.6116.088.068.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0260035
7619861200002674.098.0NaN118.088.072.018.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0270035
7619871200002782.097.0NaN120.082.066.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0280035
7619881200002886.097.0NaN123.089.065.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN239.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0290035
7619891200002976.098.036.4118.082.065.015.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0300035
7619901200003080.096.0NaN115.087.065.015.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0310035
7619911200003174.097.0NaN114.083.067.015.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0320035
7619921200003278.098.0NaN110.083.069.015.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN620NaNNaN0.0330035
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